In semiconductor exposure apparatuses for manufacturing semiconductor devices, finer and more densely integrated circuits require projected exposures at ever-higher resolutions in order to transfer the circuit pattern on a master (hereinafter referred to as a reticle) onto a silicon wafer substrate. Since the circuit pattern projection resolution is determined by the number of apertures (NA) in the projection system as well as the wavelength of the exposure, the resolution has been increased by increasing the exposure system NA and by increasing the exposure wavelength. In the latter method, the type of exposure light source wavelength used has changed from gamma rays to infrared rays, and further, is in the process of changing again from infrared rays to an excimer laser. At present, semiconductor exposure apparatuses having oscillation wavelengths of 248 nm or 193 nm have already been commercialized and are already in use.
Moreover, at present, 157 nm wavelength VUV (vacuum-ultraviolet) as well as 1.3 nm wavelength EUV (extreme-ultraviolet radiation) are currently being studied as possible exposure methods for the next generation of semiconductor exposure apparatuses.
At the same time, as circuit patterns become ever-finer, the need for high-accuracy alignment of the reticle on which the circuit pattern is formed and the wafer on which the reticle pattern is projected has also increased. The required accuracy is to within one-third of the circuit line width. Thus, for example, if the design width of the current circuit line is 180 nm, then the required accuracy of alignment is within 60 nm. In addition, a wide variety of device structures has been proposed and are under study for commercialization. As the number of personal computers in use increases, the main driving force behind circuit miniaturization has changed from the DRAM-driven memory to the CPU chip. It is likely that such miniaturization will increase with future additional advances in information technology such as household wireless LANs, Bluetooth communications systems devices, (ITS) (Intelligent Transport Systems) typified by car-mounted radars using frequencies of 77 GHz, and MMIC (Millimeter-waver Monolithic Integrated Circuits) used in LMDS (Local Multipoint Distribution Service) systems utilizing frequencies of 24-38 GHz.
Moreover, semiconductor device production processes also vary widely, from the W-CMP (Tungsten Chemical Mechanical Polishing) process that is already becoming a thing of the past to the Cu Dual Damascene process currently being eyed as planarization technologies for solving the problem of a lack of depth of focus of projection optical systems of semiconductor exposure apparatuses.
Finally, semiconductor device structures and materials also vary widely, for example, from the proposed P-HEMT (Pseudomorphic High Electron Mobility Transistor) and M-HEMT (Metamorph-HEMT) formed by combining compounds such as GaAs and InP to the proposed HBT (Heterojunction Bipolar Transistor) using SiGe, SiGeC, and the like.
Given the current state of the semiconductor industry as described above, as long as semiconductor manufacturing apparatuses, such as semiconductor exposure apparatuses, are used, the number of apparatus parameters that should be optimized is very large and depends on the exposure systems used and products produced. Moreover, these parameters are not independent of each other, but are instead closely interrelated.
Conventionally, the optimum values of the parameters are set by the device maker/purchaser of the apparatus through trial and error, which means that a substantial amount of time is required to establish these optimum values. In addition, even after the optimum values of the parameters have once been set, for example, if a process error occurs, changes in the production process dictated by the error may require changing the optimum values of the parameters of the production apparatus, which also requires a substantial amount of time.
In addition, in the production of semiconductor devices, the amount of time that can be spared from start-up to production is strictly limited, and so, of course, is the time that can be given to re-establishing the optimum values for the parameters.
Moreover, from a cost of ownership standpoint, it is necessary to improve the utilization of the production equipment, so it is therefore necessary that any changes in optimum values of parameters that have already been established should be carried out quickly. Under these circumstances, it is very difficult to manufacture a wide variety of semiconductor devices at optimum parameter values, and ultimately, even production equipment capable of obtaining a high yield, if used without optimizing the parameter values, will obtain only a sub-standard yield and lead to an overall decrease in yield for no apparent cause. Such a reduction in yield can lead to an increase in production costs and a decrease in shipments, with a consequent loss of competitiveness.